Abstract
Websites evaluating products and services are becoming quite common. The large number of evaluations form a substantial corpus that can be used to train and test sentiment analysis tools. The analyzes produced by these tools allow companies and institutions in general to make important decisions that may be vital to the institution’s future. This paper describes an implementation of the Naïve Bayes algorithm for the polarity analysis of the reviews from Rio de Janeiro hotel services, reporting the development and difficulties of the data extraction, processing and analysis methods of a corpus with 69076 comments. The results show that the tool is suitable for detecting feelings of positive and negative polarity, but does not present satisfactory results for neutral polarity.
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This research is supported in part by the funding agencies FAPEMIG, CNPq, and CAPES.
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Martins, G.S., de Paiva Oliveira, A., Moreira, A. (2017). Sentiment Analysis Applied to Hotels Evaluation. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2017. ICCSA 2017. Lecture Notes in Computer Science(), vol 10409. Springer, Cham. https://doi.org/10.1007/978-3-319-62407-5_52
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DOI: https://doi.org/10.1007/978-3-319-62407-5_52
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